Background: I have the following data:
27% of the respondents to a survey are interested in a product. Of that 27% which is interested:
- 59% are 15-24 years old.
- 18% are 25-34 years old.
- 6% are 35-44 years old.
- 4% are 45-54 years old.
- The rest are outside these age ranges.
The probability of being in each age range is:
- 11 % for 15-24.
- 13% for 25-34.
- 13% for 25-34.
- 12% for 34-45.
- rest is outside.
Problem: What percentage of each age group is interested in the new product?
Attempt: Bayes Theorem seems the right way to go here since I need to invert a probability: calling P(I)
the probability of being interested in the product and P(E)
the probability of being in a certain age range, from the survey I have P(I)
(27% are interested) and I have P(E | I)
and I want to find P(I | E)
.
So my attempt e.g. for the age group 15-24 was to do:
P(I|E ) = P(I) * P(E | I) / P(E) = 27% * 59% / 11%
27% is the overall probability of being interested in the product, 59% is the probability of being in age range 15-24 given being interested in the product.
Question: Calculating P(E)
is where I get confused. I tried using 11%, which is how much of the population is in the age range 15-24.
But it does not work, because I get a number greater than 1 as a result.
What is the correct way to calculate P(E)
in this problem and am I setting things up correctly ?